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A Database for the Radio Frequency Fingerprinting of Bluetooth Devices

Author

Listed:
  • Emre Uzundurukan

    (Department of Avionics, Atilim University, 06830 Ankara, Turkey)

  • Yaser Dalveren

    (Department of Avionics, Atilim University, 06830 Ankara, Turkey
    Department of Electronic Systems, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology, 2815 Gjøvik, Norway)

  • Ali Kara

    (Department of Electrical Electronics Engineering, Atilim University, 06830 Ankara, Turkey)

Abstract

Radio frequency fingerprinting (RFF) is a promising physical layer protection technique which can be used to defend wireless networks from malicious attacks. It is based on the use of the distinctive features of the physical waveforms (signals) transmitted from wireless devices in order to classify authorized users. The most important requirement to develop an RFF method is the existence of a precise, robust, and extensive database of the emitted signals. In this context, this paper introduces a database consisting of Bluetooth (BT) signals collected at different sampling rates from 27 different smartphones (six manufacturers with several models for each). Firstly, the data acquisition system to create the database is described in detail. Then, the two well-known methods based on transient BT signals are experimentally tested by using the provided data to check their solidity. The results show that the created database may be useful for many researchers working on the development of the RFF of BT devices.

Suggested Citation

  • Emre Uzundurukan & Yaser Dalveren & Ali Kara, 2020. "A Database for the Radio Frequency Fingerprinting of Bluetooth Devices," Data, MDPI, vol. 5(2), pages 1-11, June.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:2:p:55-:d:374392
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    References listed on IDEAS

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    1. Ramsey, Benjamin W. & Stubbs, Tyler D. & Mullins, Barry E. & Temple, Michael A. & Buckner, Mark A., 2015. "Wireless infrastructure protection using low-cost radio frequency fingerprinting receivers," International Journal of Critical Infrastructure Protection, Elsevier, vol. 8(C), pages 27-39.
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    Cited by:

    1. Joaquín Torres-Sospedra & Aleksandr Ometov, 2021. "Data from Smartphones and Wearables," Data, MDPI, vol. 6(5), pages 1-3, April.

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